bioerga-clustering

Clustering and representation methods for proteins and protein trajectories in Python using several distance metrics.

The methods are implemented using several libraries, such as

• PyEMMA (molecular dynamics (MD) analysis, featurization and Markov State Models),
• rmsd (root-mean-square deviation (RMSD) of molecules using rotation),
• mdtraj (pdb files handling),
• scikit-learn (machine learning methods in Python)

This project provides a number of tools and interfaces developed in the context of "INSPIRED-ΕΚΠΑ" which is a subproject of "INSPIRED - The National Research Infrastructures on Integrated Structural Biology, Drug Screening Efforts & Drug target functional characterization". More information can be found on bioerga the webpage of the ΕρΓΑ Lab dedicated on research in the area of applications of informatics in biology.

Dependencies

- Python (>= 3.6)
- numpy (>=1.18)
- pyEMMA (>=2.5)
- mdshare (>=0.4)
- mdtraj (>=1.9)
- rmsd (>=1.3)
- scikit-learn (>=0.23)

Instalation

pip install -r requirements.txt